N. De Stefano

Bio: N. De Stefano is an academic researcher from University of Siena. The author has contributed to research in topics: Multiple sclerosis & Medicine. The author has an hindex of 47, co-authored 128 publications receiving 19980 citations. Previous affiliations of N. De Stefano include McGill University & John Radcliffe Hospital.

Axonal damage correlates with disability in patients with relapsing-remitting multiple sclerosis. Results of a longitudinal magnetic resonance spectroscopy study.

Abstract: It has been difficult to establish a strong correlation between total brain T2-weighted lesion volume on MRI and clinical disability in multiple sclerosis, in part because of the lack of pathological specificity of T2-weighted MRI signal changes. Proton magnetic resonance spectroscopy studies have shown that measurements of the resonance intensity of N-acetylaspartate (which is localized exclusively in neurons and neuronal processes in the mature brain) can provide a specific index of axonal damage or dysfunction. Here we report a 30-month longitudinal study of 29 patients with multiple sclerosis who had either a relapsing or a secondary progressive clinical course. Conventional brain MRI and single-voxel proton magnetic resonance spectroscopy examinations were obtained at intervals of 6-8 months with concurrent clinical evaluation. At the onset of the study, the brain N-acetylaspartate:creatine resonance intensity ratio was abnormally low for the whole group of patients (control mean = 2.93 +/- 0.2, patient mean = 2.56 +/- 0.4, P < 0.005). There were no significant differences between the relapsing and secondary progressive subgroups. Over the follow-up period, there was a trend towards a decrease (8%) in the brain N-acetylaspartate:creatine ratio for the 11 relapsing patients and a significant (P < 0.001) correlation between changes in the brain N-acetylaspartate:creatine ratio and expanded disability scale scores for the patients in this group. This correlation was even more evident for the patients who had clinically relevant relapses during the 30 months of follow-up (seven of 11 patients). Increases in T2-weighted lesion volumes (35% in 30 months for the group as a whole, P < 0.0001, without differences between the subgroups) did not correlate with disability either in the group of patients as a whole or in the different subgroups. We conclude that indices of axonal damage or loss such as brain N-acetylaspartate may provide a specific measure of pathological changes relevant to disability. Total T2-weighted lesion volumes, although more sensitive to changes with time than brain N-acetylaspartate, may be less relevant to understanding the progression of disability.

Imaging axonal damage of normal-appearing white matter in multiple sclerosis.

Abstract: The current study was designed to determine the relative distribution of decreases of N-acetylasparate (NAA), a marker of axonal damage, between lesions and normal-appearing white matter of patients with established multiple sclerosis and to test for associations between changes in the ratio of NAA to creatine/phosphocreatine (NAA:Cr) in those compartments and changes in disability. Data were collected from a 30-month longitudinal study of 28 patients with either a relapsing course with partial remissons and no progression between attacks (relapsing/remitting) (11 patients) or a course of progressively increasing disability, following a period of relapsing/remitting disease (secondary progressive) (17 patients). Proton magnetic resonance spectroscopic imaging (MRSI) and conventional MRI examinations were performed at 6-8-month intervals with concurrent clinical assessments of disability. General linear models were used to test associations between MRSI, MRI, lesion volume and clinical data. Analysis confirmed that the NAA:Cr ratio is lower in lesions than in the normal-appearing white matter (-15.3% in relapsing/remitting multiple sclerosis and -8.8% in secondary progressive multiple sclerosis). The lower NAA:Cr ratio per unit lesion volume previously observed for secondary progressive relative to relapsing/remitting patients was found to result from a lower ratio (8.2%, P < 0.01) in the normal-appearing white matter rather than from any differences within lesions. The importance of changes in the normal-appearing white matter was emphasized further with the observation that the NAA:Cr ratio in the normal-appearing white matter accounted for most of the observed 15.6% (P < 0.001) decrease in the NAA:Cr ratio in the brains of relapsing/remitting patients over the period of study. The decrease in the NAA:Cr ratio in normal-appearing white matter correlated strongly (P < 0.001) with changes in disability in the relapsing/remitting subgroup. These results add to data suggesting that axonal damage or loss may be responsible for functional impairments in multiple sclerosis. The accumulation of secondary axonal damage in the normal-appearing white matter may be of particular significance for understanding chronic disability in this disease.

Normalized accurate measurement of longitudinal brain change.

Abstract: Purpose Quantitative measurement of change in brain size and shape (e.g., to estimate atrophy) is an important current area of research. New methods of change analysis attempt to improve robustness, accuracy, and extent of automation. A fully automated method has been developed that achieves high estimation accuracy. Method A fully automated method of longitudinal change analysis is presented here, which automatically segments brain from nonbrain in each image, registers the two brain images while using estimated skull images to constrain scaling and skew, and finally estimates brain surface motion by tracking surface points to subvoxel accuracy. Results and conclusion The method described has been shown to be accurate ( approximately 0.2% brain volume change error) and to achieve high robustness (no failures in several hundred analyses over a range of different data sets).

Fast robust automated brain extraction

Abstract: An automated method for segmenting magnetic resonance head images into brain and non-brain has been developed. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of MR sequences. The method, Brain Extraction Tool (BET), uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. We describe the new method and give examples of results and the results of extensive quantitative testing against "gold-standard" hand segmentations, and two other popular automated methods.

Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria

Abstract: New evidence and consensus has led to further revision of the McDonald Criteria for diagnosis of multiple sclerosis. The use of imaging for demonstration of dissemination of central nervous system lesions in space and time has been simplified, and in some circumstances dissemination in space and time can be established by a single scan. These revisions simplify the Criteria, preserve their diagnostic sensitivity and specificity, address their applicability across populations, and may allow earlier diagnosis and more uniform and widespread use.

The Brain's Default Network Anatomy, Function, and Relevance to Disease

Abstract: Thirty years of brain imaging research has converged to define the brain’s default network—a novel and only recently appreciated brain system that participates in internal modes of cognition Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations These two subsystems converge on important nodes of integration including the posterior cingulate cortex The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer’s disease